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Author | SHA1 | Date | |
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accf266be6 | ||
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30caac3a68 | ||
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60cfa728e2 | ||
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3327bb0f8d | ||
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a2d4b6fc81 |
@ -234,6 +234,7 @@ function(ggml_add_backend_library backend)
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# write the shared library to the output directory
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set_target_properties(${backend} PROPERTIES LIBRARY_OUTPUT_DIRECTORY ${CMAKE_RUNTIME_OUTPUT_DIRECTORY})
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target_compile_definitions(${backend} PRIVATE GGML_BACKEND_DL)
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add_dependencies(ggml ${backend})
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else()
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add_library(${backend} ${ARGN})
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target_link_libraries(ggml PUBLIC ${backend})
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@ -66,6 +66,26 @@
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#include "ggml-kompute.h"
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#endif
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// disable C++17 deprecation warning for std::codecvt_utf8
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#if defined(__clang__)
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# pragma clang diagnostic push
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# pragma clang diagnostic ignored "-Wdeprecated-declarations"
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#endif
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static std::wstring utf8_to_utf16(const std::string & str) {
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std::wstring_convert<std::codecvt_utf8_utf16<wchar_t>> converter;
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return converter.from_bytes(str);
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}
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static std::string utf16_to_utf8(const std::wstring & str) {
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std::wstring_convert<std::codecvt_utf8_utf16<wchar_t>> converter;
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return converter.to_bytes(str);
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}
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#if defined(__clang__)
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# pragma clang diagnostic pop
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#endif
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#ifdef _WIN32
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using dl_handle = std::remove_pointer_t<HMODULE>;
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@ -88,11 +108,6 @@ static dl_handle * dl_load_library(const std::wstring & path) {
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return handle;
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}
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static dl_handle * dl_load_library(const std::string & path) {
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std::wstring_convert<std::codecvt_utf8_utf16<wchar_t>> converter;
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return dl_load_library(converter.from_bytes(path));
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}
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static void * dl_get_sym(dl_handle * handle, const char * name) {
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DWORD old_mode = SetErrorMode(SEM_FAILCRITICALERRORS);
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SetErrorMode(old_mode | SEM_FAILCRITICALERRORS);
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@ -114,8 +129,8 @@ struct dl_handle_deleter {
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}
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};
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static void * dl_load_library(const std::string & path) {
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dl_handle * handle = dlopen(path.c_str(), RTLD_NOW | RTLD_LOCAL);
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static void * dl_load_library(const std::wstring & path) {
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dl_handle * handle = dlopen(utf16_to_utf8(path).c_str(), RTLD_NOW | RTLD_LOCAL);
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return handle;
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}
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@ -202,11 +217,11 @@ struct ggml_backend_registry {
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devices.push_back(device);
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}
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ggml_backend_reg_t load_backend(const char * path, bool silent) {
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ggml_backend_reg_t load_backend(const std::wstring & path, bool silent) {
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dl_handle_ptr handle { dl_load_library(path) };
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if (!handle) {
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if (!silent) {
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GGML_LOG_ERROR("%s: failed to load %s\n", __func__, path);
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GGML_LOG_ERROR("%s: failed to load %s\n", __func__, utf16_to_utf8(path).c_str());
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}
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return nullptr;
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}
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@ -214,7 +229,7 @@ struct ggml_backend_registry {
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auto score_fn = (ggml_backend_score_t) dl_get_sym(handle.get(), "ggml_backend_score");
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if (score_fn && score_fn() == 0) {
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if (!silent) {
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GGML_LOG_INFO("%s: backend %s is not supported on this system\n", __func__, path);
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GGML_LOG_INFO("%s: backend %s is not supported on this system\n", __func__, utf16_to_utf8(path).c_str());
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}
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return nullptr;
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}
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@ -222,7 +237,7 @@ struct ggml_backend_registry {
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auto backend_init_fn = (ggml_backend_init_t) dl_get_sym(handle.get(), "ggml_backend_init");
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if (!backend_init_fn) {
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if (!silent) {
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GGML_LOG_ERROR("%s: failed to find ggml_backend_init in %s\n", __func__, path);
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GGML_LOG_ERROR("%s: failed to find ggml_backend_init in %s\n", __func__, utf16_to_utf8(path).c_str());
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}
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return nullptr;
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}
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@ -231,16 +246,16 @@ struct ggml_backend_registry {
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if (!reg || reg->api_version != GGML_BACKEND_API_VERSION) {
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if (!silent) {
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if (!reg) {
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GGML_LOG_ERROR("%s: failed to initialize backend from %s: ggml_backend_init returned NULL\n", __func__, path);
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GGML_LOG_ERROR("%s: failed to initialize backend from %s: ggml_backend_init returned NULL\n", __func__, utf16_to_utf8(path).c_str());
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} else {
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GGML_LOG_ERROR("%s: failed to initialize backend from %s: incompatible API version (backend: %d, current: %d)\n",
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__func__, path, reg->api_version, GGML_BACKEND_API_VERSION);
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__func__, utf16_to_utf8(path).c_str(), reg->api_version, GGML_BACKEND_API_VERSION);
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}
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}
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return nullptr;
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}
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GGML_LOG_INFO("%s: loaded %s backend from %s\n", __func__, ggml_backend_reg_name(reg), path);
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GGML_LOG_INFO("%s: loaded %s backend from %s\n", __func__, ggml_backend_reg_name(reg), utf16_to_utf8(path).c_str());
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register_backend(reg, std::move(handle));
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@ -376,14 +391,14 @@ ggml_backend_t ggml_backend_init_best(void) {
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// Dynamic loading
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ggml_backend_reg_t ggml_backend_load(const char * path) {
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return get_reg().load_backend(path, false);
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return get_reg().load_backend(utf8_to_utf16(path), false);
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}
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void ggml_backend_unload(ggml_backend_reg_t reg) {
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get_reg().unload_backend(reg, true);
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}
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static std::string get_executable_path() {
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static std::wstring get_executable_path() {
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#if defined(__APPLE__)
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// get executable path
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std::vector<char> path;
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@ -401,7 +416,7 @@ static std::string get_executable_path() {
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if (last_slash != std::string::npos) {
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base_path = base_path.substr(0, last_slash);
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}
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return base_path + "/";
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return utf8_to_utf16(base_path + "/");
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#elif defined(__linux__) || defined(__FreeBSD__)
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std::string base_path = ".";
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std::vector<char> path(1024);
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@ -427,57 +442,63 @@ static std::string get_executable_path() {
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path.resize(path.size() * 2);
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}
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return base_path + "/";
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return utf8_to_utf16(base_path + "/");
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#elif defined(_WIN32)
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std::vector<char> path(MAX_PATH);
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DWORD len = GetModuleFileNameA(NULL, path.data(), path.size());
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std::vector<wchar_t> path(MAX_PATH);
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DWORD len = GetModuleFileNameW(NULL, path.data(), path.size());
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if (len == 0) {
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return "";
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return {};
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}
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std::string base_path(path.data(), len);
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std::wstring base_path(path.data(), len);
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// remove executable name
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auto last_slash = base_path.find_last_of('\\');
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if (last_slash != std::string::npos) {
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base_path = base_path.substr(0, last_slash);
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}
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return base_path + "\\";
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return base_path + L"\\";
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#else
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return {};
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#endif
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}
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static std::string backend_filename_prefix() {
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static std::wstring backend_filename_prefix() {
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#ifdef _WIN32
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return "ggml-";
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return L"ggml-";
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#else
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return "libggml-";
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return L"libggml-";
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#endif
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}
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static std::string backend_filename_suffix() {
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static std::wstring backend_filename_suffix() {
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#ifdef _WIN32
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return ".dll";
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return L".dll";
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#else
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return ".so";
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return L".so";
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#endif
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}
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static std::wstring path_separator() {
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#ifdef _WIN32
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return L"\\";
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#else
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return L"/";
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#endif
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}
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static ggml_backend_reg_t ggml_backend_load_best(const char * name, bool silent, const char * user_search_path) {
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// enumerate all the files that match [lib]ggml-name-*.[so|dll] in the search paths
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// TODO: search system paths
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std::string file_prefix = backend_filename_prefix() + name + "-";
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std::vector<std::string> search_paths;
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std::wstring file_prefix = backend_filename_prefix() + utf8_to_utf16(name) + L"-";
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std::vector<std::wstring> search_paths;
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if (user_search_path == nullptr) {
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search_paths.push_back("./");
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search_paths.push_back(L"." + path_separator());
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search_paths.push_back(get_executable_path());
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} else {
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#if defined(_WIN32)
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search_paths.push_back(std::string(user_search_path) + "\\");
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#else
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search_paths.push_back(std::string(user_search_path) + "/");
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#endif
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search_paths.push_back(utf8_to_utf16(user_search_path) + path_separator());
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}
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int best_score = 0;
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std::string best_path;
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std::wstring best_path;
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namespace fs = std::filesystem;
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for (const auto & search_path : search_paths) {
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@ -487,27 +508,27 @@ static ggml_backend_reg_t ggml_backend_load_best(const char * name, bool silent,
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fs::directory_iterator dir_it(search_path, fs::directory_options::skip_permission_denied);
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for (const auto & entry : dir_it) {
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if (entry.is_regular_file()) {
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std::string filename = entry.path().filename().string();
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std::string ext = entry.path().extension().string();
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std::wstring filename = entry.path().filename().wstring();
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std::wstring ext = entry.path().extension().wstring();
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if (filename.find(file_prefix) == 0 && ext == backend_filename_suffix()) {
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dl_handle_ptr handle { dl_load_library(entry.path().c_str()) };
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dl_handle_ptr handle { dl_load_library(entry.path().wstring()) };
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if (!handle && !silent) {
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GGML_LOG_ERROR("%s: failed to load %s\n", __func__, entry.path().string().c_str());
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GGML_LOG_ERROR("%s: failed to load %s\n", __func__, utf16_to_utf8(entry.path().wstring()).c_str());
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}
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if (handle) {
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auto score_fn = (ggml_backend_score_t) dl_get_sym(handle.get(), "ggml_backend_score");
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if (score_fn) {
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int s = score_fn();
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#ifndef NDEBUG
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GGML_LOG_DEBUG("%s: %s score: %d\n", __func__, entry.path().string().c_str(), s);
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GGML_LOG_DEBUG("%s: %s score: %d\n", __func__, utf16_to_utf8(entry.path().wstring()).c_str(), s);
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#endif
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if (s > best_score) {
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best_score = s;
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best_path = entry.path().string();
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best_path = entry.path().wstring();
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}
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} else {
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if (!silent) {
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GGML_LOG_INFO("%s: failed to find ggml_backend_score in %s\n", __func__, entry.path().string().c_str());
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GGML_LOG_INFO("%s: failed to find ggml_backend_score in %s\n", __func__, utf16_to_utf8(entry.path().wstring()).c_str());
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}
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}
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}
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@ -519,15 +540,15 @@ static ggml_backend_reg_t ggml_backend_load_best(const char * name, bool silent,
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if (best_score == 0) {
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// try to load the base backend
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for (const auto & search_path : search_paths) {
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std::string path = search_path + backend_filename_prefix() + name + backend_filename_suffix();
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std::wstring path = search_path + backend_filename_prefix() + utf8_to_utf16(name) + backend_filename_suffix();
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if (fs::exists(path)) {
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return get_reg().load_backend(path.c_str(), silent);
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return get_reg().load_backend(path, silent);
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}
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}
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return nullptr;
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}
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return get_reg().load_backend(best_path.c_str(), silent);
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return get_reg().load_backend(best_path, silent);
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}
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void ggml_backend_load_all() {
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|
@ -135,14 +135,20 @@ function(ggml_add_cpu_backend_variant_impl tag_name)
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endif()
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# show enabled features
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if (CMAKE_HOST_SYSTEM_NAME STREQUAL "Windows")
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set(FEAT_INPUT_FILE "NUL")
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else()
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set(FEAT_INPUT_FILE "/dev/null")
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endif()
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|
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execute_process(
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COMMAND ${CMAKE_C_COMPILER} ${ARCH_FLAGS} -dM -E -
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INPUT_FILE "/dev/null"
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INPUT_FILE ${FEAT_INPUT_FILE}
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OUTPUT_VARIABLE ARM_FEATURE
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RESULT_VARIABLE ARM_FEATURE_RESULT
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)
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if (ARM_FEATURE_RESULT)
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message(FATAL_ERROR "Failed to get ARM features")
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message(WARNING "Failed to get ARM features")
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else()
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foreach(feature DOTPROD SVE MATMUL_INT8 FMA FP16_VECTOR_ARITHMETIC)
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string(FIND "${ARM_FEATURE}" "__ARM_FEATURE_${feature} 1" feature_pos)
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@ -317,6 +323,11 @@ function(ggml_add_cpu_backend_variant_impl tag_name)
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target_compile_definitions(${GGML_CPU_NAME} PRIVATE ${ARCH_DEFINITIONS})
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|
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if (GGML_BACKEND_DL)
|
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if (GGML_NATIVE)
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# the feature check relies on ARCH_DEFINITIONS, but it is not set with GGML_NATIVE
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message(FATAL_ERROR "GGML_NATIVE is not compatible with GGML_BACKEND_DL, consider using GGML_CPU_ALL_VARIANTS")
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endif()
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# The feature detection code is compiled as a separate target so that
|
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# it can be built without the architecture flags
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# Since multiple variants of the CPU backend may be included in the same
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|
@ -1657,7 +1657,7 @@ bool llama_token_is_control_impl(const struct llama_vocab & vocab, llama_token t
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}
|
||||
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llama_token llama_token_bos_impl(const struct llama_vocab & vocab) {
|
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return vocab.special_bos_id;
|
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return vocab.type != LLAMA_VOCAB_TYPE_WPM ? vocab.special_bos_id : vocab.special_cls_id;
|
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}
|
||||
|
||||
llama_token llama_token_eos_impl(const struct llama_vocab & vocab) {
|
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|
@ -45,7 +45,7 @@ struct llama_vocab {
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id special_unk_id = 0;
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id special_sep_id = LLAMA_TOKEN_NULL;
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id special_pad_id = LLAMA_TOKEN_NULL;
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id special_cls_id = LLAMA_TOKEN_NULL;
|
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id special_cls_id = LLAMA_TOKEN_NULL; // TODO: revisit if this is really needed https://github.com/ggerganov/llama.cpp/pull/10930
|
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id special_mask_id = LLAMA_TOKEN_NULL;
|
||||
|
||||
id linefeed_id = 13;
|
||||
|
@ -3053,6 +3053,13 @@ struct llama_kv_cache {
|
||||
}
|
||||
};
|
||||
|
||||
// block of KV slots to move when defragging
|
||||
struct llama_kv_defrag_move {
|
||||
uint32_t src;
|
||||
uint32_t dst;
|
||||
uint32_t len;
|
||||
};
|
||||
|
||||
struct llama_control_vector {
|
||||
std::vector<struct ggml_tensor *> tensors; // per layer
|
||||
std::vector<ggml_context_ptr> ctxs;
|
||||
@ -10990,35 +10997,23 @@ struct llm_build_context {
|
||||
return gf;
|
||||
}
|
||||
|
||||
struct ggml_cgraph * build_defrag(const std::vector<uint32_t> & ids) {
|
||||
struct ggml_cgraph * build_defrag(const std::vector<struct llama_kv_defrag_move> & moves) {
|
||||
struct ggml_cgraph * gf = ggml_new_graph_custom(ctx0, llama_model_max_nodes(model), false);
|
||||
|
||||
for (uint32_t i = 0; i < ids.size(); ++i) {
|
||||
const uint32_t id = ids[i];
|
||||
|
||||
if (i == id || id == ids.size()) {
|
||||
continue;
|
||||
}
|
||||
|
||||
uint32_t nm = 1;
|
||||
|
||||
while (i + nm < ids.size() && ids[i + nm] == id + nm) {
|
||||
nm++;
|
||||
}
|
||||
|
||||
for (const auto & move : moves) {
|
||||
for (int il = 0; il < n_layer; ++il) {
|
||||
const int64_t n_embd_k_gqa = hparams.n_embd_k_gqa(il);
|
||||
const int64_t n_embd_v_gqa = hparams.n_embd_v_gqa(il);
|
||||
|
||||
ggml_tensor * view_k_src = ggml_view_2d(ctx0, kv_self.k_l[il],
|
||||
n_embd_k_gqa, nm,
|
||||
n_embd_k_gqa, move.len,
|
||||
ggml_row_size(kv_self.k_l[il]->type, n_embd_k_gqa),
|
||||
ggml_row_size(kv_self.k_l[il]->type, n_embd_k_gqa*i));
|
||||
ggml_row_size(kv_self.k_l[il]->type, n_embd_k_gqa*move.src));
|
||||
|
||||
ggml_tensor * view_k_dst = ggml_view_2d(ctx0, kv_self.k_l[il],
|
||||
n_embd_k_gqa, nm,
|
||||
n_embd_k_gqa, move.len,
|
||||
ggml_row_size(kv_self.k_l[il]->type, n_embd_k_gqa),
|
||||
ggml_row_size(kv_self.k_l[il]->type, n_embd_k_gqa*id));
|
||||
ggml_row_size(kv_self.k_l[il]->type, n_embd_k_gqa*move.dst));
|
||||
|
||||
ggml_tensor * view_v_src;
|
||||
ggml_tensor * view_v_dst;
|
||||
@ -11026,31 +11021,29 @@ struct llm_build_context {
|
||||
if (flash_attn) {
|
||||
// NOTE: the V cache is not transposed when using flash attention
|
||||
view_v_src = ggml_view_2d(ctx0, kv_self.v_l[il],
|
||||
n_embd_v_gqa, nm,
|
||||
n_embd_v_gqa, move.len,
|
||||
ggml_row_size(kv_self.v_l[il]->type, n_embd_v_gqa),
|
||||
ggml_row_size(kv_self.v_l[il]->type, n_embd_v_gqa*i));
|
||||
ggml_row_size(kv_self.v_l[il]->type, n_embd_v_gqa*move.src));
|
||||
|
||||
view_v_dst = ggml_view_2d(ctx0, kv_self.v_l[il],
|
||||
n_embd_v_gqa, nm,
|
||||
n_embd_v_gqa, move.len,
|
||||
ggml_row_size(kv_self.v_l[il]->type, n_embd_v_gqa),
|
||||
ggml_row_size(kv_self.v_l[il]->type, n_embd_v_gqa*id));
|
||||
ggml_row_size(kv_self.v_l[il]->type, n_embd_v_gqa*move.dst));
|
||||
} else {
|
||||
view_v_src = ggml_view_2d(ctx0, kv_self.v_l[il],
|
||||
nm, n_embd_v_gqa,
|
||||
move.len, n_embd_v_gqa,
|
||||
ggml_row_size(kv_self.v_l[il]->type, kv_self.size),
|
||||
ggml_row_size(kv_self.v_l[il]->type, i));
|
||||
ggml_row_size(kv_self.v_l[il]->type, move.src));
|
||||
|
||||
view_v_dst = ggml_view_2d(ctx0, kv_self.v_l[il],
|
||||
nm, n_embd_v_gqa,
|
||||
move.len, n_embd_v_gqa,
|
||||
ggml_row_size(kv_self.v_l[il]->type, kv_self.size),
|
||||
ggml_row_size(kv_self.v_l[il]->type, id));
|
||||
ggml_row_size(kv_self.v_l[il]->type, move.dst));
|
||||
}
|
||||
|
||||
ggml_build_forward_expand(gf, ggml_cpy(ctx0, view_k_src, view_k_dst));
|
||||
ggml_build_forward_expand(gf, ggml_cpy(ctx0, view_v_src, view_v_dst));
|
||||
}
|
||||
|
||||
i += nm - 1;
|
||||
}
|
||||
|
||||
//LLAMA_LOG_INFO("gf->n_nodes = %d\n", gf->n_nodes);
|
||||
@ -17601,7 +17594,7 @@ struct llm_build_context {
|
||||
}
|
||||
};
|
||||
|
||||
static struct ggml_cgraph * llama_build_graph_defrag(llama_context & lctx, const std::vector<uint32_t> & ids) {
|
||||
static struct ggml_cgraph * llama_build_graph_defrag(llama_context & lctx, const std::vector<struct llama_kv_defrag_move> & moves) {
|
||||
llama_ubatch dummy = {};
|
||||
dummy.equal_seqs = true;
|
||||
|
||||
@ -17611,7 +17604,7 @@ static struct ggml_cgraph * llama_build_graph_defrag(llama_context & lctx, const
|
||||
|
||||
llm.init();
|
||||
|
||||
struct ggml_cgraph * result = llm.build_defrag(ids);
|
||||
struct ggml_cgraph * result = llm.build_defrag(moves);
|
||||
|
||||
llm.free();
|
||||
|
||||
@ -18627,7 +18620,12 @@ static int llama_decode_internal(
|
||||
kv_self.head = 0;
|
||||
}
|
||||
|
||||
const auto slot = llama_kv_cache_find_slot(kv_self, ubatch);
|
||||
auto slot = llama_kv_cache_find_slot(kv_self, ubatch);
|
||||
if (!slot) {
|
||||
llama_kv_cache_defrag(kv_self);
|
||||
llama_kv_cache_update(&lctx);
|
||||
slot = llama_kv_cache_find_slot(kv_self, ubatch);
|
||||
}
|
||||
if (!slot) {
|
||||
return 1;
|
||||
}
|
||||
@ -19030,8 +19028,8 @@ static void llama_kv_cache_defrag_internal(struct llama_context & lctx) {
|
||||
|
||||
//const int64_t t_start = ggml_time_us();
|
||||
|
||||
// number of cells moved
|
||||
uint32_t n_moves = 0;
|
||||
// groups of cells moved
|
||||
std::vector<struct llama_kv_defrag_move> moves;
|
||||
|
||||
// each move requires 6*n_layer tensors (see build_defrag)
|
||||
// - source view, destination view, copy operation
|
||||
@ -19095,19 +19093,11 @@ static void llama_kv_cache_defrag_internal(struct llama_context & lctx) {
|
||||
// are we moving a continuous block of memory?
|
||||
bool cont = false;
|
||||
|
||||
// should we stop searching for the next move?
|
||||
bool stop = false;
|
||||
|
||||
// go back and move the nf cells to the hole
|
||||
for (; i1 < n_kv; ++i1) {
|
||||
auto & cell1 = kv_self.cells[i1];
|
||||
|
||||
if (cell1.is_empty() || ids[i1] != n_kv) {
|
||||
if (n_moves == max_moves) {
|
||||
stop = true;
|
||||
break;
|
||||
}
|
||||
|
||||
cont = false;
|
||||
continue;
|
||||
}
|
||||
@ -19123,8 +19113,10 @@ static void llama_kv_cache_defrag_internal(struct llama_context & lctx) {
|
||||
kv_self.head = n_used;
|
||||
|
||||
if (!cont) {
|
||||
n_moves++;
|
||||
moves.push_back({i1, i0 + nf, 1});
|
||||
cont = true;
|
||||
} else {
|
||||
moves.back().len++;
|
||||
}
|
||||
|
||||
nf++;
|
||||
@ -19134,22 +19126,16 @@ static void llama_kv_cache_defrag_internal(struct llama_context & lctx) {
|
||||
}
|
||||
}
|
||||
|
||||
if (stop || n_moves == max_moves) {
|
||||
break;
|
||||
}
|
||||
|
||||
//LLAMA_LOG_INFO("(tmp log) KV defrag: move [%u, %u) to [%u, %u)\n", is, i1 + 1, i0, i0 + nh);
|
||||
|
||||
i0 += nh - 1;
|
||||
}
|
||||
|
||||
if (n_moves == 0) {
|
||||
if (moves.size() == 0) {
|
||||
return;
|
||||
}
|
||||
|
||||
//LLAMA_LOG_INFO("(tmp log) KV defrag cell moves: %u\n", n_moves);
|
||||
|
||||
//LLAMA_LOG_INFO("expected gf nodes: %u\n", 6*n_moves*n_layer);
|
||||
//LLAMA_LOG_INFO("(tmp log) KV defrag cell moves: %u\n", moves.size());
|
||||
|
||||
#if 0
|
||||
// CPU defrag
|
||||
@ -19224,11 +19210,18 @@ static void llama_kv_cache_defrag_internal(struct llama_context & lctx) {
|
||||
#else
|
||||
// ggml_graph defrag
|
||||
|
||||
ggml_backend_sched_reset(lctx.sched.get());
|
||||
for (std::size_t i = 0; i < moves.size(); i += max_moves) {
|
||||
std::vector<struct llama_kv_defrag_move> chunk;
|
||||
auto end = std::min(i + max_moves, moves.size());
|
||||
chunk.assign(moves.begin() + i, moves.begin() + end);
|
||||
|
||||
ggml_cgraph * gf = llama_build_graph_defrag(lctx, ids);
|
||||
ggml_backend_sched_reset(lctx.sched.get());
|
||||
|
||||
llama_graph_compute(lctx, gf, lctx.cparams.n_threads, lctx.threadpool);
|
||||
//LLAMA_LOG_INFO("expected gf nodes: %u\n", 6*chunk.size()*n_layer);
|
||||
ggml_cgraph * gf = llama_build_graph_defrag(lctx, chunk);
|
||||
|
||||
llama_graph_compute(lctx, gf, lctx.cparams.n_threads, lctx.threadpool);
|
||||
}
|
||||
#endif
|
||||
|
||||
//const int64_t t_end = ggml_time_us();
|
||||
|
Loading…
Reference in New Issue
Block a user